TRIANGLE FUZZY TRANSFORM BASED AUTOMATIC NOISE AND COLOR IMAGE REDUCTION METHODS

TRIANGLE FUZZY TRANSFORM BASED AUTOMATIC NOISE AND COLOR IMAGE REDUCTION METHODS

Noise reduction and image reduction are very important research area forimage processing and computer vision. Many papers have been proposed fornoise and image reductions. In this paper, novel triangle fuzzy sets transform(F-transform) is proposed for color image denoising and reduction. Theproposed methods consist of histogram extraction, threshold pointscalculation, fuzzy sets construction and fuzzy tansformation phases. Firstly,histogram of the image is extracted, maximum points of histogram arecalculated, and these points are considered as threshold points. Fuzzy sets arecreated using threshold points. Then, F-transform is applied on theoverlapping and non-overlapping blocks of the images for image denoisingand reduction respectively. The main objective of the presented method are toremove random noises of the images and color image reduction withsatisfactory visual quality. In order to evaluate triangle fuzzy sets based Ftransformapplications, variable noise intensities and block sizes are used.Mean absolute error (MAE), peaks signal noise-to-ratio (PSNR) andpenalized function (PEN) are utilized for obtaining numerical results.Numerical simulations and comprasions clearly illustare that the proposedtriangle F-transform is good transformation for random noises removing andimage reduction.

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